The Art of Programming

The aim of this course is to teach students to design efficient algorithms to solve complex time- and memory-based problems. The course addresses the following topics: 1. Introduction. Why do we need this course? Problem-solving techniques. Computational thinking. How to fail your Google job interview. 2. Complexity. Quantitative algorithm analysis considering time and (memory) resource consumption. Complexity classes and asymptotic complexity. Big-Oh & Big-? notations, amortized cost, etc. 3. Algorithm design patterns. Reinventing the Wheel can be a good for a while. Many successful algorithms use similar techniques and we can use these patterns to design new algorithms: divide and conquer, greedy algorithms and dynamic programming techniques, especially blind and information-driven search techniques. Technique applicability requirements. 4. Problems, problems, problems. A synthesis of complexity and design patterns by solving wide-ranging algorithmic problems, also covering problem classification.

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Universidad Politécnica de Madrid

School of Computer Engineering

Computer Languages,Systems and Software Engineering